Agriculture is a crucial part of the Indian economy. The world’s population is rapidly growing and so is the demand for food. At the same time traditional farming methods are not adequate to feed over a billion Indians. This challenge necessitates a smart solution. As a result of this realisation, agribusinesses are embracing the implementation of Artificial Intelligence (AI) and Internet of Things (IoT) in agriculture. According to a recent analysis by Reports and Data, the value of IoT in the agricultural market is predicted to reach $30.8 billion in 2028, exhibiting a CAGR of 10.6 per cent over the forecast period. We shall examine the impact of technology in reshaping of agri-financing.
The implementation of AI and IoT technologies not only applies to agriculture in terms of crops and inputs but to agri-financing, too. While it may not be easy to view it this way, we must keep in mind that farmers are entrepreneurs too. They run a business that is constantly in demand and requires direction, strategy, and understanding of various aspects such as the crops and soil. Finally all these endeavours require financing. Unfortunately, providing credit to farmers has continued to remain a major challenge primarily due to the risk factors involved. Agritech startups today are committed to enabling farmers to build a better life for themselves by leveraging cutting-edge technologies such as AI and IoT.
Agri-financing: The key to farmer growth
Agriculture, like any other industry, relies on consistent and adequate financial support to thrive. While farmers contribute to a large chunk of the country’s GDP and economy, they, unfortunately, remain some of the most underserved communities facing multiple challenges due to a lack of infrastructure and inadequate financing. To solve this issue and bridge the gap between farmers and resources, the Agritech industry is leveraging AI and IoT-enabled technologies to ensure farmers have access to sound credit facilities.
Agri financing plays a critical role in assisting farmers in purchasing inputs, preparing and managing land, obtaining better farm equipment and machinery, and overall achieving a good crop yield. Now, although both the state and central governments have actively taken measures to ensure credit is available to farmers, on a larger, practical scale, most of it either doesn’t reach the farmers, or the processes in banks and other formal institutions are too tedious.
Assessment of farmers and other agri ecosystem participants
With novel technologies, Agritech firms can efficiently assess the creditworthiness before lending and make the process hassle-free. Agritech firms enable all important stakeholders to connect on a single, centralised platform backed by advanced technologies such as AI and IoT, making the fragmented process of agri-lending easier for both financial institutions and farmers. Thus, these innovative technologies are not just benefiting agri-finance but also the entire agribusiness.
Technology is opening up newer datasets which are enabling new methods for credit assessment. Traditionally the challenge has been to assess borrowers in the Agriculture sector because of the seasonal nature of earnings and variability. Coupled with lack of data about the agriculture scenario this used to make the sector highly risk prone. Digital interventions in the farming lifecycle generate newer datasets which are opening up new avenues of credit assessment.
Novel methods of service delivery
There are new methods of delivery arising out of the digital penetration of services. These AI enabled services provide the contextual and low cost delivery mechanism for fintech products and services. Tech platforms bring down the servicing cost to minimal leading to smaller value loans being offered and repaid digitally.
Risk Reduction in farming by reducing variability
Apart from this, AI and IoT-led technologies assist in making farming more sustainable, productive, and profitable, overall augmenting agricultural productivity.
Monitoring crops and soil
Using various IoT early warnings of potential crop failures can be generated. This helps the farmer make relevant decisions in the right time reducing the risks associated with farming. Early warnings also help the farmers in improving the quality and quantity of output
Predictive analytics
The weather undoubtedly influences crop productivity. AI offers a variety of tools for predicting changes in weather patterns and assists farmers in keeping abreast with weather forecasting data in a sophisticated way. It enables the creation of seasonal forecasting models for improved agricultural accuracy and production. The farmer can take precautions by knowing and making critical decisions about planting and harvesting, thanks to the data analysis. Implementing such a method allows farmers to make better decisions at the right moment, resulting in higher yields and revenues without jeopardising the crops.
Helps to Maximising output
The use of AI aids in the best crop selection and also helps in the selection of hybrid seed options that are best suited to the needs of farmers. It was implemented after observing how seeds react to various weather and soil conditions. The collected information helps to reduce the chances of plant diseases. It enables the farmers to meet the market trends, yearly outcomes, consumer needs, thus maximising agricultural returns cost-effectively.
Positive transformation
The combination of AI and IoT is altering agriculture’s traditional pattern, allowing it to enter the digital age. It is assisting farmers in gaining access to markets, inputs, data, advisory, and credit, as well as delivering timely and accurate data combined with analytics to help establish a robust demand-driven, efficient supply chain. The use of these technologies is becoming a tool for averting ecosystem devastation by reducing the use of soil-depleting fertilisers, as well as empowering impoverished farmers to grow their income through agri-finance.
Agriculture is a crucial part of the